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Found 4 papers, 0 papers with code
Veni, Vidi, Vici: Solving the Myriad of Challenges before Knowledge Graph Learning
Knowledge Graphs (KGs) have become increasingly common for representing large-scale linked data.
Predicting Illness for a Sustainable Dairy Agriculture: Predicting and Explaining the Onset of Mastitis in Dairy Cows
Mastitis is a billion dollar health problem for the modern dairy industry, with implications for antibiotic resistance.
Can We Detect Mastitis earlier than Farmers?
The aim of this study was to build a modelling framework that would allow us to be able to detect mastitis infections before they would normally be found by farmers through the introduction of machine learning techniques.
Release Early, Release Often: Predicting Change in Versioned Knowledge Organization Systems on the Web
To illustrate the accuracy, genericity and domain independence of the method, we study the relationship between its effectiveness and several characterizations of the evaluated datasets, finding that predictors like the number of versions in a chain and their release frequency have a fundamental impact in predictability of change in Web KOS.
